Department of Computer Science & Engineering

1. Department of Computer Science & Engineering REU 2006–Performance Analysis of Optic Flow: HD vs. Regular Video Jennifer Allen, Mentor: Dr. Dmitry Goldgof Introduction: Optic Flow Results & Analyses HD Data (JVC HD Camera, 1280 x 720) Optic flow looks for movement in an image and gives you a three dimensional output of the observed motion. Figure 9: Brightness Constancy Violations Motivation Figure 1: Start Frame Figure 2: End Frame This is the first step of an identification program that uses strain computed from facial movement as a biometric. This stage is important because poor motion estimation will lead to incorrect strain computation causing the recognition algorithm to fail. Figure 10: Smoothness Violations Figure 3: Vertical Displacement Figure 4: Horizontal Displacement Conclusions Regular Data (Canon Optura 20 Camera, 720 x 480) Goals • Best results on the HD data were around seven to eight frames difference, while on the regular data it was eight to nine frames difference. • HD output has less of a percentage of violations compared to regular data • Horizontal displacement is noisy because there is little horizontal movement • The algorithm is not as robust as it claims. Using a face detector to define a region of interest could result in more stable flow computations • To find the optimal number of frames in a video sequence that produces accurate motion fields • To find if using a HD camera produces more accurate motion fields than using a regular camera Figure 5: Start Frame Figure 6: End Frame Figure 7: Vertical Displacement Figure 8: Horizontal Displacement Department of Computer Science & Engineering